SMAC offers a robust and flexible framework for Bayesian Optimization to support users in determining well-performing hyperparameter configurations for their (Machine Learning) algorithms, datasets ...

Most previous studies on gas pipeline failure assessment are based on the basic Bayesian network (BN). However, the conditional probability table (CPT) determined by expert experience is often ...

Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Dr, Madison, Wisconsin 53706, United States ...

We then formally cast the problem of finding the best gripper parametrization within a probabilistic framework, addressing it using Bayesian Optimization tools. Numerical results on a set of ...

An interview with Karl Friston, a computational psychiatrist and an architect of an AI developed to emulate natural ...

Unfortunately, due to mathematical intractability of most Bayesian models, the reader is only shown simple, artificial examples. This can leave the user with a so-what feeling about Bayesian inference ...

The proposed paradigm combines the power of artificial neural network with Bayesian regularization technique to address the challenges associated with noisy and limited underwater sensor data. The ...

Bob Dylan famously asked, “How many roads must a man walk down, before you can call him a man?”. The power of the question is ...

Durga Prasad Katasani's insights highlight the transformative potential of predictive analytics in optimizing cloud migration ...

Researchers must choose a framework for conducting NMA (Bayesian or frequentist) and select appropriate model(s), and those conducting NMA need to understand the assumptions and limitations of ...

Google launches Meridian, an open-source marketing tool using advanced modeling to optimize ad budgets and measure campaign ...